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FinCovRegularization  

Covariance Matrix Estimation and Regularization for Finance
View on CRAN: Click here


Download and install FinCovRegularization package within the R console
Install from CRAN:
install.packages("FinCovRegularization")

Install from Github:
library("remotes")
install_github("cran/FinCovRegularization")

Install by package version:
library("remotes")
install_version("FinCovRegularization", "1.1.0")



Attach the package and use:
library("FinCovRegularization")
Maintained by
YaChen Yan
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2015-03-01
Latest Update: 2016-04-25
Description:
Estimation and regularization for covariance matrix of asset returns. For covariance matrix estimation, three major types of factor models are included: macroeconomic factor model, fundamental factor model and statistical factor model. For covariance matrix regularization, four regularized estimators are included: banding, tapering, hard-thresholding and soft- thresholding. The tuning parameters of these regularized estimators are selected via cross-validation.
How to cite:
YaChen Yan (2015). FinCovRegularization: Covariance Matrix Estimation and Regularization for Finance. R package version 1.1.0, https://cran.r-project.org/web/packages/FinCovRegularization. Accessed 06 Jun. 2026.
Previous versions and publish date:
1.0.0 (2015-03-01 08:16)
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Complete documentation for FinCovRegularization
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